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Meta-heuristic and Evolutionary Algorithms for Engineering Optimization

optimization (ACO), and the particle swarm optimization (PSO) technique. Chapter 1 of Meta-heuristic and Evolutionary Algorithms for Engineering;

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Applications of Cuckoo Search Algorithm and its Variants

in medical and engineering applications. Evolutionary-based meta-heuristic approaches are increasingly being applied to solve complicated;

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Application of Evolutionary Algorithms for Multi-objective Optimization in VLSI and Embedded Systems

This book describes how evolutionary algorithms (EA), including genetic algorithms (GA) and particle swarm optimization (PSO) can be;

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Optimization Using Evolutionary Algorithms and Metaheuristics

Optimization using Evolutionary Algorithms and Metaheuristics applications in engineering;

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Computational Intelligence Techniques and Their Applications to Software Engineering Problems

of different solve optimization problems under software engineering domain Covers heuristic as well as meta-heuristic algorithms designed to;

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Parallel Problem Solving from Nature -- PPSN XIV

optimization: why and how; evolutionary multi-objective optimization; intelligent systems for smart cities; advances on multi-modal optimization;

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A Framework for Alternation of Meta-Heuristic Algorithms

This work presents a new approach based on the alternation of meta-heuristic algorithms solving the problems of combinatorial optimization;

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Multimodal Optimization by Means of Evolutionary Algorithms

of computational intelligence, particularly those engaged with heuristic search, multimodal optimization, evolutionary computing, and experimental analysis.;

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Optimization Using Evolutionary Algorithms and Metaheuristics

applications for both single-objective and multi-objective optimization problems Offers recent developments from a variety of engineering;

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A Brief Introduction to Continuous Evolutionary Optimization

problem is available except via function evaluations. This work introduces a collection of heuristics and algorithms for black box optimization;

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Optimizing Engineering Problems through Heuristic Techniques

evolutionary heuristic techniques like genetic algorithm and particle swarm optimization Contains natural based techniques like ant colony;

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Optimizing Engineering Problems through Heuristic Techniques

Describes evolutionary heuristic techniques like genetic algorithm and particle swarm optimization Contains natural based techniques like;

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Dynamic Parameter Adaptation for Meta Heuristic Optimization Algorithms Through

In this book, a methodology for parameter adaptation in meta-heuristic op-timization methods is proposed. This methodology is based on;

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Nature-Inspired Methods for Metaheuristics Optimization

group of chapters describes in detail different meta-heuristic algorithms, and shows their applicability using some test or real-world problems;

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Classical and Recent Aspects of Power System Optimization

Classical and Recent Aspects of Power System Optimization presents conventional and meta-heuristic optimization methods and algorithms;

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Adaptive Stochastic Optimization Techniques with Applications

optimization, decision analysis, intelligent systems, evolutionary programming, heuristic optimization, stochastic and adaptive dynamic programming;

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Deep Statistical Comparison for Meta-heuristic Stochastic Optimization Algorithms

. Part II: Deep Statistical Comparison of meta-heuristic stochastic optimization algorithms - Chapters 5-7. Part III: Implementation and;

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Evolutionary Algorithms In Engineering And Computer Science

Evolutionary Algorithms in Engineering and Computer Science Edited by K. Miettinen, University of Jyvaskyla, Finland M. M. Makela;

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Evolutionary Optimization Algorithms

with a firm grasp of the basic principles of EAs. Covering the theory, history, mathematics, and applications of evolutionary optimization;

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Evolutionary Learning

to the heuristic nature of evolutionary optimization, most outcomes to date have been empirical and lack theoretical support. This;

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Applications of Flower Pollination Algorithm and its Variants

find optimal solution for a variety of real-world engineering and medical problems. Swarm intelligence-based meta-heuristic algorithms are;

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Applications of Bat Algorithm and its Variants

application to find optimal solutions for a variety of real-world engineering and medical problems. Today, swarm intelligence-based meta-heuristic;

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Optimization Problems in Graph Theory

classes * A general technique for heuristic algorithms for optimization problems * The network design problem with cut constraints * Algorithms;

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MultiObjective Optimization using Evolutionary Algorithms

Evolutionary algorithms are relatively new, but very powerful techniques used to find solutions to many real--world search and optimization;

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Advances in Heuristic Signal Processing and Applications

application problems, with a special emphasis on heuristic iterative optimization methods employing modern evolutionary and swarm intelligence based;

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Applied Evolutionary Algorithms for Engineers using Python

This book meant for those who seek to apply evolutionary algorithms to problems in engineering and science. To this end, it provides the;

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Classical and Evolutionary Algorithms in the Optimization of Optical Systems

the implementation of the classical and evolutionary algorithms in the program for the optimization of optical systems. Every chapter in this;

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